Optimization in Brain? - Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms

Changxu Wu (), Marc Berman () and Yili Liu ()
Additional contact information
Changxu Wu: State University of New York (SUNY)
Marc Berman: University of Michigan
Yili Liu: University of Michigan

Chapter Chapter 9 in Computational Neuroscience, 2010, pp 157-179 from Springer

Abstract: Abstract Here we present a novel approach to model brain and behavioral phenomena of multitask performance, which integrates queuing networks with reinforcement learning algorithms. Using the queuing network as the static platform of brain structure and reinforcement learning as the dynamic algorithm to quantify the learning process, this model successfully accounts for several behavioral phenomena related to the learning process of transcription typing and the psychological refractory period (PRP). This model also proposes brain changes that may accompany the typing and PRP practice effects that could be tested empirically with neuroimaging. All of the modeled phenomena emerged as outcomes of the natural operations of the human information processing queuing network.

Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-88630-5_9

Ordering information: This item can be ordered from
http://www.springer.com/9780387886305

DOI: 10.1007/978-0-387-88630-5_9

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().